Abstract T MP54: Hospital Characteristics Associated with Advanced Primary Stroke Center Designation

Stroke ◽  
2014 ◽  
Vol 45 (suppl_1) ◽  
Author(s):  
Catherine McDonald ◽  
Steven Cen ◽  
Lucas Ramirez ◽  
William J Mack ◽  
Nerses Sanossian
Keyword(s):  
Systems Of Care ◽  
Improve Patient Care ◽  
Federal State ◽  
National Guidelines ◽  
American Hospital ◽  
American Hospital Association ◽  
Community Provider ◽  
Primary Stroke Center ◽  
Stroke Center ◽  
Hospital Characteristics

Background: Organized stroke systems of care, including accreditation of hospitals as primary stroke centers (PSC), are meant to improve patient care and compliance with national guidelines. Nationwide, less than a third of eligible hospitals have achieved advanced certification in stroke. We aimed to characterize hospital factors associated with achievement of stroke center certification. Methods: We utilized the 2011 American Hospital Association survey to obtain data on hospital characteristics. Only hospitals with ≥ 25 beds and 24-hour emergency departments were evaluated. The Joint Commission (TJC), Healthcare Facilities Accreditation Program and DNV Healthcare websites were used to determine certification status of each hospital as a primary stroke center. All comprehensive SC were considered as PSC. Factors found to be associated with achievement of certification (P<0.010) were evaluated by logistic regression to determine a final model of independent association. Results: Of the 3696 hospitals to complete the survey, 3069 fulfilled study criteria, including 908 PSC (31%) and 2161 non-PSC. PSC were larger (mean 354 vs. 136 beds), had busier EDs (56,000 vs. 24,000 visits/year), were more often affiliated with ACGME residency programs (43% vs. 14%), AMA medical schools (51% vs. 21%), TJC-accreditation (95% vs. 65%), inpatient neurological services (94% vs. 46%) and trauma centers (55% VS 38%); and were less likely to be governmental (Federal/State/County 10% vs. 26%) and designated sole community provider (1% vs 9%). Independent hospital characteristics associated with PSC certification were TJC accreditation (OR 3.5, 95%CI 2.4-5.0), sole community provider (OR 0.22, 0.10-0.47), hospital type (governmental vs. non 0.61, 0.44-0.84), increasing size (per quartile in number of beds OR 2.5, 2.1-3.1) and neurological services (OR 3.2, 2.4-4.6). Conclusions: PSC hospitals are larger non-governmental hospitals with availability of neurological services. Increasing the low numbers of governmental (i.e. County or State) hospital achievement of PSC may be a potential area of focus.

Abstract W P311: Demographic and Regional Characteristics Associated With Advanced Primary Stroke Center Designation

Stroke ◽  
2014 ◽  
Vol 45 (suppl_1) ◽  
Author(s):  
Catherine McDonald ◽  
Steven Cen ◽  
Lucas Ramirez ◽  
William J Mack ◽  
Nerses Sanossian
Keyword(s):  
Univariate Analysis ◽  
American Hospital ◽  
American Hospital Association ◽  
Healthcare Facilities ◽  
For Profit ◽  
Home Value ◽  
Regional Factors ◽  
Stroke Center ◽  
Zip Code ◽  
Hospital Characteristics

Background: Nationwide less than a third of eligible hospitals have achieved advanced certification in stroke, and there may be disparities affecting less affluent areas serving a higher proportion of minorities. We aimed to characterize demographic and regional factors associated with achievement of stroke center certification while controlling for hospital characteristics. Methods: We linked the 2011 American Hospital Association survey of hospital characteristics to the 2010 national census for population and household data by region. Emergency medical services stroke routing data was obtained from communication with state and county contact. Only hospitals with ≥ 25 beds and 24-hour emergency departments were evaluated. The Joint Commission, Healthcare Facilities Accreditation Program and DNV Healthcare websites were used to determine certification status of each hospital. We controlled for hospital bed size, teaching affiliation (AMA, ACGME), emergency department volume, rural designation, hospital type (governmental/for-profit/nonprofit), and trauma center designation in analysis. Results: Of the 3696 hospitals to complete the survey, the 3069 fulfilling study criteria included 908 PSC (31%) and 2161 non-PSC. In univariate analysis PSC hospitals were located in areas with greater population in immediate vicinity (29, 316 vs. 20,901, p<0.0001), greater proportion of minorities (73% white, 16% black, 15% Hispanic vs. 80%/12%/11%, p<0.0001), greater number of households per zip code (11,540 vs. 8050, p<0.0001) and a higher regional mean income ($52,112 vs. $46,262, p<0.0001) and higher home value ($234,000 vs. $170,000, p<0.0001). More PSC hospitals were located in regions with preferential EMS routing of stroke (52% vs. 40%). While controlling for hospital-based factors, the demographic and regional factors independently associated with hospital PSC designation were number of households per zip code (per 1000 households OR 1.1, 95%CI 1.0-1.2), increasing Hispanic population (every 10% increase OR 1.1, 1.0-1.2), and income per household (per $10,000 OR 1.2, 1.1-1.3). Conclusions: Hospitals achieving PSC designation are located in more affluent and densely populated areas with higher population of Hispanic residents.

Abstract WP318: Mortality Among Newly Certified Stroke Centers and Other Hospitals in the U.S.

Stroke ◽  
2017 ◽  
Vol 48 (suppl_1) ◽  
Author(s):  
Shumei Man ◽  
Jesse D Schold ◽  
Ken Uchino
Keyword(s):  
Metastatic Cancer ◽  
Stroke Care ◽  
Prior History ◽  
Medicare Beneficiaries ◽  
American Hospital ◽  
American Hospital Association ◽  
Annual Survey ◽  
Primary Stroke Center ◽  
Short Term Mortality ◽  
Stroke Center

Introduction: Primary Stroke Center (PSC) certification was established to improve stroke care. The numbers of PSCs have significantly increased in the past decade. However, it remains unclear whether PSC certification has any impact on stroke mortality. We examined the short term mortality of hospitals that received initial PSC certification between 2009 and 2013 (new PSCs), compared to those received PSC certification before 2009 (existing PSCs) and those never received PSC certification (NSCs). Method: The inclusion criteria was Medicare beneficiaries aged ≥65 years who were hospitalized between January 1, 2009 to December 31, 2013 with a primary discharge diagnosis of ischemic stroke. The patient information were obtained from the Medicare Provider Analysis and Review (MEDPAR) file. The list and characteristics of hospitals were obtained from the American Hospital Association Annual Survey Database. This study included only those general hospitals with emergency departments. All statistical analyses were performed using SAS Version 9.4 software. Results: Among 1165,960 Medicare beneficiaries included in this study, 28.9% were treated at 2640 NSCs, 24.6% were treated at 634 new PSCs, and 46.6% were treated at 785 existing PSCs. Higher percentages of patients at new and existing PSCs had complicated hypertension, myocardial infarction, congestive heart failure, atrial fibrillation, prior history of cerebrovascular disease, any malignancy, metastatic cancer, peripheral artery disease and smoking (p<0.0001). New PSCs had the lowest unadjusted in-hospital all-cause mortality, followed by NSCs and existing PSCs (4.2%, 4.6% and 5% respectively). Both New and existing PSC groups had lower unadjusted 30 day compared to NSCs (12.5%, 13.2% and 13.7%). New PSCs had lower unadjusted and adjusted 30 day mortality than existing PSCs (Hazard Ratio 0.981, 95% Confidence Interval (0.968, 0.993)). Conclusion: The PSCs that were newly certified between 2009 and 2013 had lower unadjusted in-hospital and 30 day mortality after stroke than existing PSCs and NSCs. It is important to further understand whether this difference results from change in patient population or quality of care.

Association of partial nephrectomy and presence of robotic surgery for kidney cancer in the United States.

2014 ◽  
Vol 32 (4_suppl) ◽  
pp. 484-484
Author(s):  
Steven V. Kardos ◽  
Brian Shuch ◽  
Peter Schulam ◽  
Quoc-Dien Trinh ◽  
Maxine Sun ◽  
...  
Keyword(s):  
Robotic Surgery ◽  
Partial Nephrectomy ◽  
Multivariable Analysis ◽  
The United States ◽  
Population Based ◽  
Cancer Center ◽  
Treatment Technology ◽  
American Hospital ◽  
American Hospital Association ◽  
Hospital Characteristics

484 Background: While hospital and surgeon characteristics are associated with the type of nephrectomy performed for renal cell carcinoma (RCC), it is unknown whether hospital presence of robotic surgery increases the likelihood of patients receiving partial nephrectomy (PN). Therefore, we evaluate the relationship of PN and hospital presence of robotic surgery from a population-based cohort in the U.S. Methods: After merging the Nationwide Inpatient Sample (NIS) and the American Hospital Association (AHA) survey from 2006 to 2008, we identified 21,999 patients who underwent either PN or radical nephrectomy (RN) for RCC. The primary outcome of this study was the type of nephrectomy performed. Multivariable logistic regression was used to identify hospital characteristics associated with receipt of PN, after adjusting for patient case mix. Results: Overall, we identified 4,832 (22.0%) and 16,347 (88.0%) patients who were surgically treated for RCC with PN and RN, respectively. On multivariable analysis, patients undergoing surgery were more likely to receive PN at academic (OR: 2.77;p<0.001), urban (OR: 3.66; p<0.001), and American College of Surgeon (ACOS) designated cancer centers (OR: 1.10; p<0.05) compared to non-academic, rural, and non-designated hospitals, respectively. After adjusting for patient and hospital characteristics, patients undergoing surgery at hospitals with presence of robotic surgery were also associated with higher adjusted odds ratios for receipt of PN compared to those treated at hospitals without the presence of this advanced treatment technology (OR: 1.28; p<0.001). Conclusions: While academic status and urban locations are established characteristics influencing the type of nephrectomy performed for RCC, ACOS cancer center designation and hospital presence of robotic surgery were also associated with higher use of PN. Our results are informative in identifying key hospital characteristics which may facilitate greater adoption of PN.

DISSEMINATION AND CHARACTERISTICS OF ACUTE CARE FOR ELDERS (ACE) UNITS IN THE UNITED STATES

2003 ◽  
Vol 19 (1) ◽  
pp. 220-227 ◽  
Author(s):  
Ravishankar Jayadevappa ◽  
Bernard S. Bloom ◽  
Donna Brady Raziano ◽  
Risa Lavizzo-Mourey
Keyword(s):  
Logistic Regression ◽  
Acute Care ◽  
Average Length ◽  
The Elderly ◽  
The United States ◽  
Economic Benefits ◽  
Stepwise Logistic Regression ◽  
American Hospital ◽  
American Hospital Association ◽  
Hospital Characteristics

Objective: The objective of this paper is to determine prevalence and characteristics of acute care for elders (ACE) units and hospital characteristics associated with the presence of an ACE unit.Methods: Data on characteristics and prevalence of ACE units were obtained by surveying all established geriatric medical divisions across U.S. medical schools. Data on hospital characteristics such as number of beds, revenue, number of Medicare inpatients, and average length of stay were obtained from the 1999 American Hospital Association Annual Survey Data. Descriptive statistics and t test were used to analyze the characteristics of ACE units. Stepwise logistic regression was used to analyze the hospital characteristics associated with the presence of an ACE unit.Results: The survey identified 16 geriatric divisions and programs with ACE units. Hospitals that have ACE units differ significantly with respect to number of beds and total revenue, compared with institutions that do not have an ACE unit. Stepwise logistic regression indicated total hospital revenue was the only factor significantly associated with the presence of an ACE unit.Conclusions: ACE units are attractive interdisciplinary models to address the particular needs of the elderly during their hospital stay. Low presence of ACE units warrants further research as to reasons more hospitals have not included them, given the available evidence for clinical, functional, and economic benefits.

Abstract W P286: Assessing Wisconsin Hospitals’ Capacity to Treat Acute Stroke

Stroke ◽  
2015 ◽  
Vol 46 (suppl_1) ◽  
Author(s):  
Julie E Baumann
Keyword(s):  
Acute Stroke ◽  
Technical Assistance ◽  
Systems Of Care ◽  
Stroke Care ◽  
Self Report ◽  
The Status ◽  
Primary Stroke Center ◽  
Stroke Systems Of Care ◽  
Stroke Center ◽  
Reported Data

Introduction: Establishing regional stroke systems of care can improve timely treatment and survival, and reduce disability and related healthcare costs for persons experiencing acute stroke. A well-functioning stroke system requires seamless coordination between EMS, hospitals and certified stroke centers. Of 127 non-specialty hospitals in Wisconsin, 2% are comprehensive stroke centers and 24% have achieved primary stroke center certification. However, little is known about other hospitals’ capacity to treat acute stroke. The Wisconsin Stroke Coalition (WSC) wanted to better understand the need to improve stroke care capacity among hospitals not certified to treat stroke. The hypothesis was that few non-stroke certified hospitals in Wisconsin have all the criteria in place to treat acute stroke. Methods: WSC developed a short survey based on the Brain Attack Coalition’s recommendations for an acute stroke-ready hospital (ASRH). The tool included a user-friendly checklist that captured the status of each recommendation; in place currently or within six months; could be developed with assistance; or no plan to develop. WSC distributed the survey to 88 non-specialty, non-stroke certified hospitals and requested that each self-report their level of stroke care. Results: Fifty-nine percent of hospitals responded to the survey. Among respondents, 5% reported having all recommendations in place within six months, 53% reported having some of the recommendations in place and 1% reported no plan to develop any of the recommendations. While only a few had implemented every recommendation, the majority either had in place or were receptive to adopting individual suggestions. Nearly half of respondents reported having telestroke in place (either by phone, with video, or both). Conclusions: According to self-reported data, non-specialty, non-stroke certified hospitals in Wisconsin appear well-positioned or receptive to developing basic recommendations for acute stroke-ready hospitals. WSC plans to disseminate findings to Wisconsin hospitals and gather further information about technical assistance that would improve their level of stroke care and coordination with EMS.

Abstract WP340: Impact of Increasing Primary Stroke Center Transfers on Comprehensive Stroke Center Capacity

Stroke ◽  
2020 ◽  
Vol 51 (Suppl_1) ◽  
Author(s):  
Jane Holl ◽  
Andy Cai ◽  
Lauren Ha ◽  
Alin Hulli ◽  
Melina Paan ◽  
...  
Keyword(s):  
Systems Of Care ◽  
Vessel Occlusion ◽  
Capacity Limits ◽  
Transfer Rates ◽  
Primary Stroke Center ◽  
Comprehensive Stroke Center ◽  
Stroke Systems Of Care ◽  
Stroke Center ◽  
Occupancy Rates ◽  
Bed Occupancy Rates

Introduction: Given the time-sensitive benefits of acute stroke (AS) treatments, stroke systems of care must balance reducing door-in-door-out (DIDO) time at primary stroke centers (PSCs) with capacity limits at comprehensive stroke centers (CSCs). For example transferring more AS patients earlier in the process (e.g., prior vascular imaging for large vessel occlusion) from PSCs would result in more inappropriate transfers to CSCs that could overburden these centers.We conducted a simulation to estimate the balance between increased AS transfers from PSCs to CSCs and the percent of CSC time on “bypass” (inability to accept transfers to neuro-ICU). Methods: Clinicians from 3 Chicago-area CSCs and 3 affiliated PSCs and the Chicago Emergency Medical Services (EMS) created a PSC DIDO process map. We assumed CSC time on bypass is affected by AS and non-AS admissions from the CSC and from the affiliated PSCs. Input data were obtained fromtheChicago region registry (e.g., # PSC to CSC transfers), peer reviewed literature (US average transfer rate of AS patients to CSCs), EMS (PSC-CSC affiliations), and CSCs (e.g., average bed occupancy rates). CSC size was estimated by #neuro-ICU beds: small (12 beds), medium (23 beds), and large (28 beds). The simulation output was % time of CSC on “bypass”. Results: Table shows % time of CSC on bypass by varying PSC AS transfer rates for each category of CSC size. Larger increases in PSC transfer rates resulted in modest increases in CSC bypass rates, particularly for medium and large CSCs. Validation with data from one CSC showed < 4% overestimate of CSC % time on bypass. Conclusion: CSCs with more beds have efficiencies of scale leading to lower % time on bypass, even with increases in PSC AS transfer rates proportionate to CSC size. This model allows stroke systems of care to compute regional CSCs’ % time on bypass based on actual PSCs’ transfer rates and CSC size.

Abstract P124: Stroke Patient Transfer Destination is Influenced by Hospital Affiliation

Stroke ◽  
2021 ◽  
Vol 52 (Suppl_1) ◽  
Author(s):  
Kori S Zachrison ◽  
Viviana Amati ◽  
Lee H Schwamm ◽  
Zhiyu Yan ◽  
Victoria Nielsen ◽  
...  
Keyword(s):  
Systems Of Care ◽  
Patient Transfers ◽  
Network Characteristics ◽  
Event Modeling ◽  
Primary Object ◽  
Stroke Systems Of Care ◽  
Stroke Center ◽  
Hospital Affiliation ◽  
Hospital Characteristics

Background: Acute ischemic stroke (AIS) patients are frequently transferred between hospitals, however it is not clear whether these transfers are optimized with respect to proximity and quality of the destination hospital. Our primary object was to identify hospital characteristics associated with sending and receiving AIS patients. Methods: Using a comprehensive statewide dataset, we identified all AIS patient transfers occurring between all 78 Massachusetts (MA) hospitals from 2007 and 2015. Hospital variables included hospital quality reputation (US News & World Report), hospital capabilities (stroke center status, annual stroke volume, and trauma center designation), and institutional affiliations (same vs. not). We also included network variables to control for the structure of hospital-to-hospital transfers. We used relational event modeling to account for complex temporal and relational dependencies associated with patient transfers. This method decomposes events into a decision to transfer, and if so, the receiving hospital destination, and models them using a discrete-choice framework. Results: Among 73,114 AIS admissions in MA during the 8-year study period, there were 7,189 (9.8%) transfers. After accounting for travel time between hospitals and structural network characteristics, factors associated with increased likelihood of being a receiving hospital included teaching hospital status, hospitals of the same or higher quality, the same or higher stroke center status, and the same hospital affiliation (Table). Conclusion: Patients experiencing AIS in MA are frequently transferred between hospitals. After accounting for multiple relevant hospital characteristics, hospital affiliation remains an important factor in determining transfer destination. While there may be some benefits to hospital affiliation, stroke systems of care should be designed to maximize patient benefit and leverage interfacility transfer accordingly.

The effect of guidelines, policy initiatives, and feedback tools on hospital adherence with the 12-node measure for colon cancer.

2013 ◽  
Vol 31 (31_suppl) ◽  
pp. 65-65
Author(s):  
Jennifer L. Paruch ◽  
Ryan P. Merkow ◽  
Mila H. Ju ◽  
David Porter Winchester ◽  
Clifford Y. Ko ◽  
...  
Keyword(s):  
Colon Cancer ◽  
Hospital Performance ◽  
National Cancer Data Base ◽  
Process Measures ◽  
American Hospital ◽  
American Hospital Association ◽  
Cancer Data ◽  
Policy Initiatives ◽  
Academic Hospitals ◽  
Hospital Characteristics

65 Background: Examination of > = 12 lymph nodes after colectomy is one of few surgical process measures. Several initiatives have targeted this measure; one tool developed by the Commission on Cancer (CoC) provides benchmarked feedback on hospital performance (CP3R). Our objectives were to (1) examine changes in measure performance over time in response to guidelines, policy initiatives, and feedback, and (2) identify hospital characteristics associated with failure to improve adherence. Methods: Patients having surgery for Stage I-III colon cancer (1990-2010) were identified from the National Cancer Data Base (NCDB). For hospital-level analyses, NCDB and American Hospital Association (2010) data were merged. Hospital CP3R use was obtained from the user log system. Multivariable logistic regression adjusted for age and tumor factors was used to identify hospital characteristics associated with adherence in 2009-2010 (> = 12 nodes in > 80% of patients). Results: The percentage of patients with > = 12 nodes removed increased from 31.5% in 1990 to 84.1% in 2010 (p < 0.0001). The percentage of adherent hospitals increased from 2.2% in 1990 to 70% in 2010 (p < 0.0001). The steepest increase in adherence occurred with introduction of CP3R. Median CP3R use increased from 5 to 57 logins annually (2005-2010). Hospital predictors of poor adherence included low volume, community hospital type, private ownership, rural location, and lower number of specialists (Table). Conclusions: Guidelines, policy initiatives, and feedback tools have helped dramatically increase adherence with the 12-node measure, but small, non-academic hospitals have been slower to improve. Additional efforts are needed to understand barriers and improve adherence at these facilities. [Table: see text]

scholarly journals Information technology to support patient engagement: where do we stand and where can we go?

2017 ◽  
Vol 24 (6) ◽  
pp. 1088-1094 ◽  
Author(s):  
Daniel M Walker ◽  
Cynthia J Sieck ◽  
Terri Menser ◽  
Timothy R Huerta ◽  
Ann Scheck McAlearney
Keyword(s):  
Information Technology ◽  
Health Information Technology ◽  
Health Information ◽  
Patient Engagement ◽  
Ontology Mapping ◽  
Hospital System ◽  
American Hospital ◽  
American Hospital Association ◽  
Ordered Logit Model ◽  
Hospital Characteristics

Abstract Objective Given the strong push to empower patients and make them partners in their health care, we evaluated the current capability of hospitals to offer health information technology that facilitates patient engagement (PE). Materials and Methods Using an ontology mapping approach, items from the American Hospital Association Information Technology Supplement were mapped to defined levels and categories within the PE Framework. Points were assigned for each health information technology function based upon the level of engagement it encompassed to create a PE-information technology (PE-IT) score. Scores were divided into tertiles, and hospital characteristics were compared across tertiles. An ordered logit model was used to estimate the effect of characteristics on the adjusted odds of being in the highest tertile of PE-IT scores. Results Thirty-six functions were mapped to specific levels and categories of the PE Framework, and adoption of each item ranged from 23.5 to 96.7%. Hospital characteristics associated with being in the highest tertile of PE-IT scores included medium and large bed size (relative to small), nonprofit (relative to government nonfederal), teaching hospital, system member, Midwest and South regions, and urban location. Discussion Hospital adoption of PE-oriented technology remains varied, suggesting that hospitals are considering how technology can create partnerships with patients. However, PE functionalities that facilitate higher levels of engagement are lacking, suggesting room for improvement. Conclusion While hospitals have reached modest levels of adoption of PE technologies, consistent monitoring of this capacity can identify opportunities to use technology to facilitate engagement.

The Relationship between Hospital Characteristics and the Cost of Hospital Care

2000 ◽  
Vol 13 (4) ◽  
pp. 256-263 ◽  
Author(s):  
Patrick Asubonteng Rivers ◽  
Sejong Bae
Keyword(s):  
Hospital Care ◽  
American Hospital ◽  
American Hospital Association ◽  
Annual Survey ◽  
Hospital Executives ◽  
The Cost ◽  
The Relationship ◽  
Hospital Characteristics

This article examines the relationship between hospital characteristics and costs of hospital care, using the 1991 American Hospital Association Annual Survey of Hospitals. The results discussed herein have implications for hospital executives, researchers and policymakers.

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